AI & Data Strategy
We offer companies new market opportunities through the use of cutting-edge technologies and AI-based data analysis processes.
In an age when digital permeates every aspect of our daily lives, it is surprising to discover how many companies continue to rely on outdated and ineffective document management systems. Yet there are still very many companies that have trucks full of paper documents such as shipping bills and contracts traveling from one location to another, often hundreds of miles apart. A veritable mountain of paper that then has to be hand-scanned and digitized before being returned to the sender.
And we are not talking about small businesses, far from it. Not only is this process expensive and slow, it also has a significant environmental impact and a high risk of human error.
But there is also good news, and that is that the technology to transform this situation exists and is absolutely established: automated document management, supported by Intelligent Document Processing (IDP) solutions and technologies such as OCR, NLP, ML, and AI, now offers an alternative that provides efficiency, security, and sustainability.
Paper-based document management is a traditional method that many companies still use to store, retrieve, and manage information. However, this method has many disadvantages. Let us look at them together:
High costs: physical document management results in high printing, storage, and transportation costs;
Reduced efficiency: time spent retrieving and managing physical documents can significantly reduce employee productivity;
High risk of error: manual document management is susceptible to errors, which can be costly and time-consuming to detect and correct;
Environmental impact: the production, transportation and disposal of paper documents have a significant impact on the environment.
Adopting an automated document management system offers numerous benefits as a result:
Cost reduction: eliminating the need for physical materials and reducing the staff required for document management can mean huge savings;
Improved efficiency: automation allows documents to be processed at much higher speeds than manual handling, thus improving overall productivity;
Enhanced security: digital solutions offer significant improvements in document security, including reducing the risk of loss, theft or damage;
Accessibility and retrieval: digital documents can be easily stored and retrieved from centralized databases, improving accessibility and reducing search time;
Environmental sustainability: minimizing paper use helps reduce tree cutting and CO2 emissions associated with paper production and transportation.
The transformation from a paper-based to a digital, automated system is facilitated by the adoption of several advanced technologies:
Optical Character Recognition (OCR): enables the conversion of printed or handwritten text into editable digital data;
Natural Language Processing (NLP): helps understand and interpret human language within documents;
Machine Learning (ML) and Artificial Intelligence (AI): are used to automate the process of classifying, categorizing, and analyzing documents;
Large Language Models (LLM) and Retrieval-Augmented Generation (RAG): offer powerful tools for improving the interpretation and generation of document content;
Transitioning from paper to digital management is not only a strategic move to reduce costs and improve efficiency, it is also an ethical imperative to promote environmental sustainability. Existing technologies offer the solutions needed to achieve this transformation, making the document management process more secure, faster and less costly.
If you would like to learn more about automated document management or discover the steps needed to digitize and automate this crucial process within your company, please contact us using the form at the bottom of this page.
In the business-to-business (B2B) context, technological innovation has radically transformed the way companies manage document workflows, especially in documentation-intensive industries such as energy, finance, and healthcare. Automated document management, combined with artificial intelligence (AI), offers revolutionary solutions to long-standing problems related to operational efficiency, cost reduction, and human resource optimization.
Modern companies are faced with the need to process ever-increasing volumes of documents. These documents, which vary widely in type and content, require processing that often relies on standardized and repetitive procedures. Effective classification of documents is therefore a primary challenge, given the need to correctly identify the "document class" to which they belong in order to proceed with appropriate processing.
Take, for example, the back office of an electric utility: the volume and variety of communications to be handled are enormous, and include contracts, invoices, fault reports, and more. Accurate classification of these documents is critical to ensure that they are routed correctly and processed efficiently.
The document management process begins with the receipt of documents, followed by their automatic categorization through the use of machine learning (ML) modules that assign confidence to the classification. This approach allows effective preprocessing of responses and targeted forwarding to the corresponding departments. File processing is then handled more smoothly, with constant monitoring to identify areas for improvement.
The proposed solution includes the use of ML-based classifiers for document categorization, automated response generators optimized through generative AI for preliminary drafting of responses, and automation platforms for file sorting. These tools, integrated into a modular and pluggable architecture, promise significant improvement in document management efficiency.
Key features of this technology solution include modular architecture for easy integration with existing systems, no-code paradigm for democratized access to the technology, and the ability to operate in the cloud for greater scalability. Extension through Robotic Process Automation (RPA) further simulates human interventions, reducing the workload on employees and allowing them to focus on more value-added tasks.
The adoption of automated and artificial intelligence-based solutions in document management offers B2B companies the opportunity to overcome challenges related to document classification and processing. Through the implementation of advanced technologies, companies can expect significant improvements in efficiency, cost reduction, and customer satisfaction. In this new technological landscape, continuous innovation will be the key to maintaining a competitive advantage, making it critical for companies to stay current on the latest trends and solutions in document management and artificial intelligence.
